Development of a genetic algorithm for maximizing wind power integration rate into the electric grid

Abstract

In this paper, a new method was proposed with the objective of maximizing the rate of wind power integration into the electric grid. This method was based on the optimization of the parameters of the turbine governors (TGs) by means of a genetic algorithm. The tuning of TGs' parameters was formulated relying on an objective function aiming at reaching the maximum wind power penetration rate. The dynamic grid modeling consisted of synchronous machines, regulators, and wind turbines. The IEEE 14-bus modified test system was adopted to test the grid using the Power System Analysis Toolbox. The simulation results revealed that, with the optimized TGs' parameters, the rate of wind power integration improved considerably.

The method for calculation and optimization of parameters of synchronous electric machines with permanent magnets as part of the generating and driving complexes

“…In the proposed method, when performing optimization based on a genetic algorithm, the starting construction of components and parts of the action machine is taken from the results of multi-criteria optimization, then segmentation of elements of an autonomous power plant in vertical and horizontal directions (2D image) is performed [14]. The symmetry of the structure is taken into account to reduce the amount of computational operations.…”

Maximum Power Extraction and Pitch Angle Control for Offshore Wind Turbine with Open-Loop Hydraulic Transmission

“…Another crucial factor affecting the output power is the control system in the variable speed and pitch wind turbine [9,10]. Considering the strong nonlinear nature of the wind turbine dynamics, some advanced intelligent controllers have been designed in the conventional mechanical wind energy transmission [11,12]. In [13], authors have employed fuzzy logic controller to regulate the rotational speed of the wind turbine rotor through controlling the electromagnetic torque.…”